An application of neural network in post-occupancy evaluation of underground stations

Abstract: "The architectural and construction design deals very often with the word quality. This term is so vague and broad that the main difficulty arises if one needs to determine its aspects. It is rather simple to deal with the quantifiable building standards. The problem is how to demystify and thereafter integrate this fuzzy concept of quality into design.
As an example we will use underground stations as a design problem area for two reasons. First of all, these spaces are rather young structures that have a high potential in the future. The efficiency of underground transport and importance of multiple space usage in the densely built urban areas are only some benefits that these spaces can offer. But yet many realized underground projects were not satisfactory to the users. Second reason lies in a fact that these spaces have their own limitations. Some qualities that are so obvious for the aboveground buildings, such as daylight or view, are rather difficult to obtain in underground spaces. Therefore, in these spaces the word quality is even more sensitive. But the literature that the architects can consult regarding these problems is rather scattered and difficult to obtain. One of the reasons is a lack of detailed documentation on actual applications of the theories followed by the research results and applied techniques. In this paper we used the AI technique, a Neural Network, for data analysis.
The main objective of this paper is to develop a Support Model that will enable quality measurement of underground spaces in a systematic way. In order to avoid the ad-hoc design solutions for underground spaces, there is a need for systematic approach to their design. In such way the intuitive approach to problem solving can be minimized. This paper deals with following topics:
1. aspects that determine the quality of space
2. classification of psychological and spatial aspects
3. development of conceptual framework
4. application of Neural Network for post-occupancy evaluation
5. results and endeavor design guidelines
First three topics will deal with criteria definition, which were necessary for design of the experimental part of a research. The experimental research, which was carried out at the site of one underground station, provided the necessary data. The main emphasis of the paper will be on Neural Network application (topic 4), which will be used to treat the data gathered on underground station. The main objective is to verify the consistency of the outcomes against the predefined criteria."